ArticleSubstance abuse : research and treatment2019
Predicting Dropout from Inpatient Substance Use Disorder Treatment: A Prospective Validation Study of the OQ-Analyst.
Article in Substance abuse : research and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01891045 (Addiction Treatment Dropout Prevention - Impact of Online Patient Feedback), which is not on this map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Addiction Treatment Dropout Prevention - Impact of Online Patient Feedback (OQ-45.2) to Therapist
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Substance Use Disorder Treatment Outcomes: Methodological Overview of Metrics and Criteria.International journal of methods in psychiatric research · 2025Pooled it
- Pretreatment social network characteristics relate to increased risk of dropout and unfavorable outcomes among women in a residential treatment setting for substance use.Journal of substance abuse treatment · 2020Trial
- Moving Beyond Self-Report in Characterizing Drug Addiction: Using Drug-Biased Behavior to Predict Treatment Completion and Dropout in Heroin-Primary, Medication-Maintained Opioid Use Disorder.Biological psychiatry global open science · 2026Article
- Article
- Gradual improvement in functioning and mental distress during long-term outpatient SUD treatment - A prospective pre-post study.Addictive behaviors reports · 2024Article
- Barriers, perceived benefits and preferences to exercise in adults with an opioid use disorder in the U.S.Preventive medicine reports · 2023Article
- A Prospective Biopsychosocial Repeated Measures Study of Stress and Dropout from Substance Addiction Treatment.Substance abuse and rehabilitation · 2023Article
- The impact of poly-traumatization on treatment outcomes in young people with substance use disorders.BMC psychiatry · 2021Article
- Antisocial Personality Disorder Among Patients in Treatment for Alcohol Use Disorder (AUD): Characteristics and Predictors of Early Relapse or Drop-Out.Substance abuse and rehabilitation · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsThere is an urgent need for tools allowing therapists to identify patients at risk of dropout. The OQ-Analyst, an increasingly popular computer-based system, is used to track patient progress and predict dropout. However, we have been unable to find empirical documentation regarding the ability of OQ-Analyst to predict dropout. The aim of the present study was to perform the first direct test of the ability of the OQ-Analyst to predict dropout.
designPatients were consecutively enlisted in a naturalistic, prospective, longitudinal clinical trial. As interventions based on feedback from the OQ-Analyst could alter the outcome and potentially render the prediction wrong, feedback was withheld from patients and therapists.
settingThe study was carried out during 2011-2013 in an inpatient substance use disorder clinic in Oslo, Norway.
participantsPatients aged 18 to 28 years who met criteria for a principal diagnosis of mental or behavioural disorder due to psychoactive substance use (ICD 10; F10.2-F19.2). MEASUREMENTS: Red signal (predictions of high risk) from the Norwegian version of the OQ-Analyst were compared with dropouts identified using patient medical records as the standard for predictive accuracy.
findingsA total of 40 patients completed 647 OQ assessments resulting in 46 red signals. There were 27 observed dropouts, only one of which followed after a red signal. Patients indicated by the OQ-Analyst as being at high risk of dropping out were no more likely to do so than those indicated as being at low risk. Random intercept logistic regression predicting dropout from a red signal was statistically nonsignificant. Bayes factor supports no association.
conclusionsThe study does not support the predictive ability of the OQ-Analyst for the present patient population. In the absence of empirical evidence of predictive ability, it may be better not to assume such ability.
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